# number of nodes
p=40
# number of edge in general network
m1=70
# the difference between the number of edges in individual networks and general network
m2=20
# number of subjects
n=60set.seed(1)
aa=lglasso(data=ddata,lambda = 0.01,trace=T)
#> [1] "iteration 1 precision difference: 3.648 /correlation tau difference: 0.133"
#> [1] "iteration 2 precision difference: 1.936 /correlation tau difference: 1.589"
#> [1] "iteration 3 precision difference: 1.753 /correlation tau difference: 1.405"
#> [1] "iteration 4 precision difference: 1.212 /correlation tau difference: 1.271"
#> [1] "iteration 5 precision difference: 1.183 /correlation tau difference: 0.978"
#> [1] "iteration 6 precision difference: 0.756 /correlation tau difference: 0.942"
#> [1] "iteration 7 precision difference: 0.738 /correlation tau difference: 0.567"
#> [1] "iteration 8 precision difference: 0.368 /correlation tau difference: 0.557"
#> [1] "iteration 9 precision difference: 0.363 /correlation tau difference: 0.25"
#> [1] "iteration 10 precision difference: 0.14 /correlation tau difference: 0.247"
#> [1] "iteration 11 precision difference: 0.138 /correlation tau difference: 0.089"
#> [1] "iteration 12 precision difference: 0.046 /correlation tau difference: 0.088"
#> [1] "iteration 13 precision difference: 0.046 /correlation tau difference: 0.029"
#> [1] "iteration 14 precision difference: 0.015 /correlation tau difference: 0.029"
#> [1] "iteration 15 precision difference: 0.014 /correlation tau difference: 0.009"
#> [1] "iteration 16 precision difference: 0.005 /correlation tau difference: 0.009"
#saveRDS(aa,file="homoOneStageResult.rds")
## estimated network
estimates=lapply(aa$wi,function(ll){ifelse(abs(ll)>10^(-3),1,0)})
estimates
#> [[1]]
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 1 1 0 1 1 0 0 0 0 0 1 1 0 0 0 0 1 1
#> V2 0 1 0 1 1 0 1 0 0 0 1 1 1 0 0 0 0 1 0 1 1
#> V3 0 0 1 1 1 1 1 1 0 0 0 1 0 0 0 0 0 0 1 1 1
#> V4 1 1 1 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0
#> V5 1 1 1 0 1 1 0 0 0 0 0 0 1 0 1 0 1 0 1 0 0
#> V6 0 0 1 0 1 1 1 1 0 1 0 0 0 1 0 1 1 0 0 0 0
#> V7 1 1 1 0 0 1 1 0 1 0 1 0 0 1 0 1 0 0 0 1 1
#> V8 1 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0
#> V9 0 0 0 1 0 0 1 0 1 1 0 1 1 1 0 0 1 0 0 1 0
#> V10 0 0 0 0 0 1 0 0 1 1 1 0 0 0 0 1 0 0 0 1 0
#> V11 0 1 0 0 0 0 1 1 0 1 1 0 0 0 1 1 0 0 0 1 0
#> V12 0 1 1 0 0 0 0 0 1 0 0 1 1 0 0 0 1 1 0 0 0
#> V13 0 1 0 0 1 0 0 0 1 0 0 1 1 1 0 0 0 1 0 0 1
#> V14 1 0 0 0 0 1 1 0 1 0 0 0 1 1 0 0 0 1 0 0 0
#> V15 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 0 0 1 0
#> V16 0 0 0 1 0 1 1 0 0 1 1 0 0 0 0 1 0 0 0 0 0
#> V17 0 0 0 0 1 1 0 0 1 0 0 1 0 0 0 0 1 1 0 0 0
#> V18 0 1 0 1 0 0 0 1 0 0 0 1 1 1 0 0 1 1 1 0 1
#> V19 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0
#> V20 1 1 1 1 0 0 1 0 1 1 1 0 0 0 1 0 0 0 0 1 0
#> V21 1 1 1 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1
#> V22 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 0 1
#> V23 1 0 1 0 1 0 0 1 1 1 1 1 0 1 0 0 1 1 0 0 1
#> V24 1 1 0 1 1 1 1 0 1 1 1 0 1 1 1 0 0 0 1 1 1
#> V25 1 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0
#> V26 0 1 1 1 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0
#> V27 0 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 1 1 0 1 0
#> V28 1 1 1 1 1 1 0 0 0 0 0 1 0 1 1 0 1 1 0 1 1
#> V29 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0
#> V30 1 1 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1
#> V31 0 1 1 1 0 1 1 1 1 0 1 1 1 1 1 1 0 0 0 1 1
#> V32 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 1
#> V33 1 1 1 0 0 1 0 1 0 0 0 0 0 1 0 1 0 1 1 0 0
#> V34 0 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 1 0 0 0 1
#> V35 0 1 0 0 1 1 1 0 0 0 1 1 1 0 1 0 0 0 0 0 1
#> V36 1 1 0 1 1 0 1 0 0 0 1 0 0 1 0 0 0 1 1 0 1
#> V37 0 1 1 1 1 0 1 0 0 0 1 0 0 0 0 0 1 1 1 1 0
#> V38 1 0 0 1 0 0 1 1 0 1 0 0 1 1 0 1 1 0 1 0 0
#> V39 1 0 1 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1 0 0
#> V40 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 1 1 1 0 0 1 0 1 0 0 1 0 0 1 0 1 1 0
#> V2 1 0 1 0 1 0 1 1 1 1 0 1 1 1 1 1 0 0 0
#> V3 0 1 0 1 1 0 1 0 1 1 0 1 1 0 0 1 0 1 0
#> V4 0 0 1 0 1 0 1 0 0 1 0 0 1 0 1 1 1 1 0
#> V5 0 1 1 0 1 0 1 0 0 0 0 0 0 1 1 1 0 0 1
#> V6 0 0 1 0 0 0 1 0 1 1 0 1 0 1 0 0 0 0 0
#> V7 0 0 1 0 0 1 0 0 0 1 0 0 0 1 1 1 1 0 0
#> V8 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0 0 1 0 0
#> V9 1 1 1 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0
#> V10 0 1 1 1 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0
#> V11 0 1 1 0 1 0 0 0 0 1 0 0 1 1 1 1 0 0 0
#> V12 1 1 0 0 0 1 1 0 0 1 1 0 1 1 0 0 0 0 1
#> V13 0 0 1 0 0 0 0 0 1 1 0 0 1 1 0 0 1 0 0
#> V14 0 1 1 0 0 0 1 0 0 1 1 1 1 0 1 0 1 1 0
#> V15 0 0 1 0 0 1 1 1 0 1 0 0 1 1 0 0 0 1 0
#> V16 0 0 0 0 1 0 0 0 0 1 0 1 0 0 0 0 1 0 0
#> V17 1 1 0 1 0 1 1 0 0 0 0 0 1 0 0 1 1 0 0
#> V18 0 1 0 0 0 1 1 0 0 0 0 1 0 0 1 1 0 1 0
#> V19 1 0 1 1 0 0 0 0 0 0 1 1 0 0 1 1 1 1 1
#> V20 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 1 0 0 0
#> V21 1 1 1 0 0 0 1 0 1 1 1 0 1 1 1 0 0 0 0
#> V22 1 1 0 0 1 0 1 0 0 1 0 0 1 0 0 1 1 1 1
#> V23 1 1 1 1 1 0 0 0 1 0 1 1 1 1 1 1 1 1 1
#> V24 0 1 1 1 0 1 1 0 0 1 0 1 0 1 1 1 1 0 0
#> V25 0 1 1 1 0 1 0 0 0 1 1 1 0 1 0 0 1 1 1
#> V26 1 1 0 0 1 0 1 0 0 1 0 0 0 1 0 1 1 1 0
#> V27 0 0 1 1 0 1 1 1 1 1 0 0 0 1 0 0 0 1 0
#> V28 1 0 1 0 1 1 1 1 0 1 0 0 1 1 1 1 1 0 0
#> V29 0 0 0 0 0 1 1 1 1 1 1 0 0 0 1 0 1 1 0
#> V30 0 1 0 0 0 1 0 1 1 1 1 0 0 1 0 1 1 0 1
#> V31 1 0 1 1 1 1 1 1 1 1 0 1 1 1 0 0 0 1 1
#> V32 0 1 0 1 0 0 0 1 1 0 1 0 0 1 0 0 0 1 1
#> V33 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 0 1 1 0
#> V34 1 1 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 1 0
#> V35 0 1 1 1 1 1 1 0 1 1 1 0 1 1 0 0 0 1 0
#> V36 0 1 1 0 0 0 1 1 0 0 0 0 0 0 1 0 1 0 0
#> V37 1 1 1 0 1 0 1 0 1 0 0 0 0 0 0 1 1 1 0
#> V38 1 1 1 1 1 0 1 1 1 0 0 1 0 0 1 1 1 1 0
#> V39 1 1 0 1 1 1 0 1 0 1 1 1 1 1 0 1 1 1 1
#> V40 1 1 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 1 1
## true network
dd$network
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V3 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
#> V5 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V6 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V8 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1 0 1 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 1 1 0 0 0 1 0 0 1 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0
#> V12 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0
#> V14 0 0 0 0 0 0 1 1 1 0 0 0 1 1 0 0 0 1 0 0 0
#> V15 1 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V16 0 0 0 1 0 1 1 0 0 1 1 0 0 0 0 1 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 1
#> V19 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0
#> V20 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V21 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V25 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V26 0 1 0 0 1 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0
#> V28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V30 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0
#> V33 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0
#> V34 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V37 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V40 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 1 0
#> V3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 1
#> V6 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0
#> V8 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V12 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V13 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
#> V15 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V16 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V17 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V19 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1
#> V20 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0
#> V23 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V24 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
#> V26 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> V27 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V28 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 0 0 1 1 0 1 0 0 0 1 0 0 0 0
#> V30 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 1
#> V33 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0
#> V37 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V38 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V39 1 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V40 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1
## correlation parameter
aa$tau
#> [1] 1.771347
aa$ll
#> [1] 19.10515set.seed(1)
aa=lglasso(data=ddata,lambda = 0.01,random=TRUE,trace=T)
#> [1] "alpha estimate: 1"
#> [1] "iteration 1 precision difference: 1.478 /correlation alpha difference: 5.796"
#> [1] "alpha estimate: 6.79566343782216"
#> [1] "iteration 2 precision difference: 0.175 /correlation alpha difference: 8.679"
#> [1] "alpha estimate: 15.4751066564369"
#> [1] "iteration 3 precision difference: 0.162 /correlation alpha difference: 0.396"
#> [1] "alpha estimate: 15.8708854280835"
#> [1] "iteration 4 precision difference: 0.153 /correlation alpha difference: 1.728"
#> [1] "alpha estimate: 14.1429926220806"
#> [1] "iteration 5 precision difference: 0.146 /correlation alpha difference: 1.117"
#> [1] "alpha estimate: 13.0255602372045"
#> [1] "iteration 6 precision difference: 0.124 /correlation alpha difference: 1.197"
#> [1] "alpha estimate: 11.828987782098"
#> [1] "iteration 7 precision difference: 0.114 /correlation alpha difference: 0.954"
#> [1] "alpha estimate: 10.8746885496785"
#> [1] "iteration 8 precision difference: 0.125 /correlation alpha difference: 0.827"
#> [1] "alpha estimate: 10.0472961652831"
#> [1] "iteration 9 precision difference: 0.096 /correlation alpha difference: 0.28"
#> [1] "alpha estimate: 9.76697338267776"
#> [1] "iteration 10 precision difference: 0.067 /correlation alpha difference: 0.509"
#> [1] "alpha estimate: 9.25837524687701"
#> [1] "iteration 11 precision difference: 0.075 /correlation alpha difference: 0.536"
#> [1] "alpha estimate: 8.7227818934082"
#> [1] "iteration 12 precision difference: 0.049 /correlation alpha difference: 0.34"
#> [1] "alpha estimate: 8.38243408782067"
#> [1] "iteration 13 precision difference: 0.056 /correlation alpha difference: 0.164"
#> [1] "alpha estimate: 8.21830572200703"
#> [1] "iteration 14 precision difference: 0.06 /correlation alpha difference: 0.256"
#> [1] "alpha estimate: 7.96185581827743"
#> [1] "iteration 15 precision difference: 0.055 /correlation alpha difference: 0.175"
#> [1] "alpha estimate: 7.7871842626904"
#> [1] "iteration 16 precision difference: 0.086 /correlation alpha difference: 0.014"
#> [1] "alpha estimate: 7.80159095380885"
#> [1] "iteration 17 precision difference: 0.035 /correlation alpha difference: 0.129"
#> [1] "alpha estimate: 7.67231920715004"
#> [1] "iteration 18 precision difference: 0.052 /correlation alpha difference: 0.125"
#> [1] "alpha estimate: 7.54751314924805"
#> [1] "iteration 19 precision difference: 0.041 /correlation alpha difference: 0.11"
#> [1] "alpha estimate: 7.43722171288938"
#> [1] "iteration 20 precision difference: 0.053 /correlation alpha difference: 0.042"
#> [1] "alpha estimate: 7.47946029825347"
#> [1] "iteration 21 precision difference: 0.04 /correlation alpha difference: 0.064"
#> [1] "alpha estimate: 7.41499307521063"
#> [1] "iteration 22 precision difference: 0.036 /correlation alpha difference: 0.151"
#> [1] "alpha estimate: 7.56587119269837"
#> [1] "iteration 23 precision difference: 0.045 /correlation alpha difference: 0.029"
#> [1] "alpha estimate: 7.53717859605908"
#> [1] "iteration 24 precision difference: 0.05 /correlation alpha difference: 0.101"
#> [1] "alpha estimate: 7.4362241684775"
#> [1] "iteration 25 precision difference: 0.033 /correlation alpha difference: 0.032"
#> [1] "alpha estimate: 7.46785119158903"
#> [1] "iteration 26 precision difference: 0.031 /correlation alpha difference: 0.088"
#> [1] "alpha estimate: 7.38030410972224"
#> [1] "iteration 27 precision difference: 0.039 /correlation alpha difference: 0.032"
#> [1] "alpha estimate: 7.34858460039623"
#> [1] "iteration 28 precision difference: 0.031 /correlation alpha difference: 0.054"
#> [1] "alpha estimate: 7.40209089454052"
#> [1] "iteration 29 precision difference: 0.044 /correlation alpha difference: 0.049"
#> [1] "alpha estimate: 7.45132320379011"
#> [1] "iteration 30 precision difference: 0.036 /correlation alpha difference: 0.006"
#> Algorithm reached the maximum iteration!
saveRDS(aa,file="heterOneStageResult.rds")
## estimated network
estimates=lapply(aa$wi$wiList,function(ll){ifelse(abs(ll)>10^(-3),1,0)})
estimates
#> list()
## true network
dd$network
#> $pre
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 1 0 0 0 0 1 0 0 0 0 0 0 0
#> [2,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [3,] 0 0 1 1 0 0 0 0 0 0 1 1 0
#> [4,] 0 0 1 1 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 1 0 0 0 0 0 0 0 0
#> [6,] 1 0 0 0 0 1 0 0 0 0 0 1 0
#> [7,] 0 0 0 0 0 0 1 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 1 0 1 0 0 0
#> [9,] 0 0 0 0 0 0 0 0 1 0 1 0 0
#> [10,] 0 0 0 0 0 0 0 1 0 1 0 1 0
#> [11,] 0 0 1 0 0 0 0 0 1 0 1 1 0
#> [12,] 0 0 1 0 0 1 0 0 0 1 1 1 0
#> [13,] 0 0 0 0 0 0 0 0 0 0 0 0 1
#> [14,] 0 0 1 0 0 0 1 0 0 0 0 0 1
#> [15,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [16,] 0 0 0 0 0 1 1 0 0 1 0 0 0
#> [17,] 0 1 0 0 0 0 0 0 0 1 0 0 0
#> [18,] 0 0 1 0 0 0 0 0 0 1 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [20,] 0 0 0 0 0 0 0 0 0 0 1 0 0
#> [21,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [23,] 1 0 1 0 0 0 0 0 0 0 0 0 0
#> [24,] 0 0 1 0 1 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 0 0 0 1 0
#> [26,] 0 0 0 0 0 0 0 1 0 1 0 1 1
#> [27,] 0 0 1 0 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 0 0 0 0 0 0 1 0 1 0 0
#> [29,] 0 0 0 0 0 0 0 0 0 0 0 1 0
#> [30,] 0 0 0 0 0 0 0 0 0 0 0 0 1
#> [31,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [32,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [33,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [34,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [35,] 0 0 0 0 0 1 0 0 0 0 1 0 0
#> [36,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [38,] 0 0 0 0 0 0 0 0 0 1 0 0 0
#> [39,] 0 1 0 0 0 0 0 0 0 0 0 1 0
#> [40,] 0 0 0 0 0 0 0 0 0 0 1 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
#> [1,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [2,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [3,] 1 0 0 0 1 0 0 0 0 1 1 0
#> [4,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [6,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [7,] 1 0 1 0 0 0 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [9,] 0 1 0 0 0 0 0 0 1 0 0 0
#> [10,] 0 0 1 1 1 0 0 0 0 0 0 0
#> [11,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 1
#> [13,] 1 0 0 0 0 0 0 0 0 0 0 0
#> [14,] 1 0 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [17,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 1 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 1 0 0 0 1 0 0
#> [20,] 0 0 0 0 0 0 1 0 0 0 0 1
#> [21,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [23,] 0 0 0 0 0 1 0 0 0 1 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [25,] 0 0 0 0 0 0 1 0 0 0 0 1
#> [26,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [27,] 0 0 0 1 0 0 0 0 0 1 0 0
#> [28,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [30,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [32,] 0 0 1 0 0 0 1 0 0 1 0 0
#> [33,] 1 0 0 0 0 0 1 0 0 0 0 0
#> [34,] 0 1 0 0 0 0 0 0 0 0 0 1
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [37,] 0 0 1 0 0 1 0 0 0 0 0 0
#> [38,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [39,] 1 0 0 0 0 0 0 0 1 0 1 0
#> [40,] 0 0 0 0 0 0 0 0 0 0 0 1
#> [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
#> [1,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [3,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [7,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [8,] 1 0 0 0 0 0 0 0 0 0 0 0
#> [9,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [10,] 1 0 0 0 0 0 0 0 0 0 0 0
#> [11,] 0 0 1 0 0 0 0 0 0 1 0 0
#> [12,] 1 0 0 1 0 0 0 0 0 0 0 0
#> [13,] 1 0 0 0 1 0 0 0 0 0 0 0
#> [14,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [15,] 1 0 0 0 0 0 0 0 1 0 0 0
#> [16,] 0 0 0 0 0 0 1 0 0 0 0 1
#> [17,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 0 0 0 1
#> [20,] 0 0 0 0 0 0 1 1 0 0 0 0
#> [21,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 1 0 0 0 0 1 0 0 0 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [26,] 1 0 1 0 0 0 0 0 0 0 0 0
#> [27,] 0 1 0 0 1 0 0 1 0 0 0 0
#> [28,] 1 0 1 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 1 1 0 0 0 0 0 0 0
#> [30,] 0 1 0 1 1 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 1 0 0 0 0 0 0
#> [32,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [33,] 0 1 0 0 0 0 0 1 0 0 1 0
#> [34,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [35,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [36,] 0 0 0 0 0 0 0 1 0 0 1 0
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 1
#> [38,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [39,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [40,] 0 1 0 0 0 0 1 0 0 0 0 0
#> [,38] [,39] [,40]
#> [1,] 0 0 0
#> [2,] 0 1 0
#> [3,] 0 0 0
#> [4,] 0 0 0
#> [5,] 0 0 0
#> [6,] 0 0 0
#> [7,] 0 0 0
#> [8,] 0 0 0
#> [9,] 0 0 0
#> [10,] 1 0 0
#> [11,] 0 0 1
#> [12,] 0 1 0
#> [13,] 0 0 0
#> [14,] 0 1 0
#> [15,] 0 0 0
#> [16,] 0 0 0
#> [17,] 0 0 0
#> [18,] 0 0 0
#> [19,] 0 0 0
#> [20,] 0 0 0
#> [21,] 0 0 0
#> [22,] 0 1 0
#> [23,] 0 0 0
#> [24,] 0 1 0
#> [25,] 0 0 1
#> [26,] 0 0 0
#> [27,] 0 0 1
#> [28,] 0 0 0
#> [29,] 0 0 0
#> [30,] 0 0 0
#> [31,] 0 0 0
#> [32,] 0 0 1
#> [33,] 0 0 0
#> [34,] 0 0 0
#> [35,] 0 0 0
#> [36,] 0 0 0
#> [37,] 0 0 0
#> [38,] 1 0 0
#> [39,] 0 1 0
#> [40,] 0 0 1
aa$ll
#> [1] 48.36001
## correlation parameter
model <- lm(dd$tau ~ aa$tau)
plot(aa$tau,dd$tau,xlab = "estimated tau",ylab="true tau")
abline(model, col = "red", lwd = 2)summary(model)
#>
#> Call:
#> lm(formula = dd$tau ~ aa$tau)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -0.164932 -0.018982 0.005359 0.013064 0.158432
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) -0.012445 0.008943 -1.392 0.169
#> aa$tau 1.573142 0.051692 30.433 <2e-16 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 0.04377 on 58 degrees of freedom
#> Multiple R-squared: 0.9411, Adjusted R-squared: 0.9401
#> F-statistic: 926.2 on 1 and 58 DF, p-value: < 2.2e-16set.seed(1)
aa=lglasso(data=ddata,lambda = c(0.1,0.1),group = group,trace=T)
#> [1] "iteration 1 precision difference: 0.796 /correlation tau difference: 0.337"
#> [1] "iteration 2 precision difference: 0.511 /correlation tau difference: 1.893"
#> [1] "iteration 3 precision difference: 0.511 /correlation tau difference: 1.099"
#> [1] "iteration 4 precision difference: 0.07 /correlation tau difference: 1.038"
#> [1] "iteration 5 precision difference: 0.07 /correlation tau difference: 0.225"
#> [1] "iteration 6 precision difference: 0.014 /correlation tau difference: 0.222"
#> [1] "iteration 7 precision difference: 0.014 /correlation tau difference: 0.026"
#> [1] "iteration 8 precision difference: 0.001 /correlation tau difference: 0.026"
#> [1] "iteration 9 precision difference: 0.002 /correlation tau difference: 0.003"
saveRDS(aa,file="homoTwoStageResult.rds")
estimates=lapply(aa$wi,function(ll){ifelse(abs(ll)>10^(-3),1,0)})
## pre-treatment network estimate
estimates[[1]]
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V17 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V33 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V35 1 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1 0 0 0 1
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V4 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V15 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V23 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V24 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V26 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V28 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V33 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V37 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## true post-treatment network
dd$network$pre
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0
#> V2 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V3 0 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V8 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1 0
#> V9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0
#> V10 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0
#> V11 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V12 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 0
#> V14 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V17 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 1 0 0 0
#> V19 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0
#> V20 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 1 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V24 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 1 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 1 1 0 1 0 0 0 0 0 1 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0
#> V40 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V7 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V9 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V13 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0
#> V15 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V16 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V21 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V23 0 1 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0
#> V24 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> V25 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V26 0 0 1 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V28 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 0 0 1 0
#> V29 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 0 0 0
#> V30 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 1
#> V31 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0
#> V32 0 1 0 0 0 0 1 1 0 0 1 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V36 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0
#> V37 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0
#> V39 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 1 0
#> V40 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 1
aa$ll
#> [1] 22.4274
## post-treatment network estimate
estimates[[2]]
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V17 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V21 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V33 0 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V35 1 0 1 0 0 0 1 1 0 1 0 1 1 0 0 0 1 0 0 0 1
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V4 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V15 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V23 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V24 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V25 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V26 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V28 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V33 1 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 1 0 1 1 0 0 0 0 0 0 0 1 0 1 0 1 0 1 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V37 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## true post-treatment network
dd$network$post
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0
#> V2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V3 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0
#> V4 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V8 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V11 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V12 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0
#> V14 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 1 0 1 1 1 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V16 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0
#> V17 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 1 0 0 1 0 0 1 0 1 0 0 0 0 0
#> V20 0 1 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V24 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V27 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0
#> V32 0 1 0 0 0 1 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0
#> V40 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0
#> V3 0 0 0 1 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0
#> V4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V7 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V9 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V13 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 1 0
#> V15 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V16 0 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V19 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V21 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 0
#> V24 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> V25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V26 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1
#> V27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V28 0 0 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 1 0
#> V29 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 0 0 0
#> V30 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 1
#> V31 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0
#> V32 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V37 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0
#> V39 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 1 0 0
#> V40 0 0 1 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## correlation parameters
aa$tau
#> [1] 2.2277904 0.9964643set.seed(1)
dd=Simulate(type="longiheter",n=n,p=p,m1=m1,m2=m2,tt=20,alpha=0.5,group=2)
ddata=do.call(rbind,dd$data)
subjects=fct_inorder(ddata$subject)
group=c(rep(0,nrow(ddata)/2),rep(1,nrow(ddata)/2))
heterTwoStageData=list(data=ddata,group=group)
saveRDS(heterTwoStageData,file="heterTwoStageData.rds")set.seed(1)
aa=lglasso(data=ddata,lambda = c(0.1,0.1),random=T,group = group,trace=T)
#> [1] "alpha estimate: 1"
#> [1] "iteration 1 precision difference: 0.708 /correlation alpha difference: 0.195"
#> [1] "alpha estimate: 1.19512436978389"
#> [1] "iteration 2 precision difference: 0.205 /correlation alpha difference: 0.384"
#> [1] "alpha estimate: 0.811223304176149"
#> [1] "iteration 3 precision difference: 0.066 /correlation alpha difference: 0.101"
#> [1] "alpha estimate: 0.710522890084319"
#> [1] "iteration 4 precision difference: 0.026 /correlation alpha difference: 0.021"
#> [1] "alpha estimate: 0.689553991757097"
#> [1] "iteration 5 precision difference: 0.016 /correlation alpha difference: 0.015"
#> [1] "alpha estimate: 0.675005938899547"
#> [1] "iteration 6 precision difference: 0.005 /correlation alpha difference: 0.006"
saveRDS(aa,file="heterTwoStageResult.rds")
estimates=lapply(aa$wi,function(ll){ifelse(abs(ll)>10^(-3),1,0)})
## pre-treatment network estimate
estimates[[1]]
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V5 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V18 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V21 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V28 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V35 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V14 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V26 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V28 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
#> V29 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V38 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## true pre-treatment network
dd$network$pre
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [2,] 0 1 0 0 0 0 0 0 0 0 1 0 1
#> [3,] 0 0 1 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 1 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 1 0 0 0 0 1 0 0 0
#> [6,] 0 0 0 0 0 1 0 0 0 0 0 0 1
#> [7,] 0 0 0 0 0 0 1 0 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 1 0 0 1 0 1
#> [9,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [10,] 0 0 0 0 1 0 0 0 0 1 0 0 0
#> [11,] 0 1 0 0 0 0 0 1 0 0 1 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 1 0
#> [13,] 0 1 0 0 0 1 0 1 0 0 0 0 1
#> [14,] 0 0 1 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 0 0 0 0 0 0 0 0 1 1
#> [17,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [18,] 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [20,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [21,] 1 0 0 1 0 0 1 0 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 1 0 1 1 0 0 0
#> [23,] 0 0 1 0 0 1 0 0 1 0 0 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [26,] 0 0 0 0 0 0 0 0 1 1 0 0 0
#> [27,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [28,] 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [30,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 0 0 0 0 1 0 0 1
#> [32,] 0 0 0 0 0 0 1 0 0 0 0 0 1
#> [33,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [34,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 0 0 0 0 0 0 0 0 0 0 0 0 1
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [38,] 0 0 1 0 0 0 0 1 0 0 0 0 0
#> [39,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [40,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
#> [1,] 0 0 0 0 1 0 0 1 0 0 0 0
#> [2,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [3,] 1 0 0 0 0 0 0 0 0 1 0 0
#> [4,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [7,] 0 0 0 0 0 0 0 1 1 0 0 0
#> [8,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [9,] 0 0 0 0 0 1 0 0 1 1 0 0
#> [10,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [11,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [12,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [14,] 1 0 0 1 0 0 0 0 0 0 1 0
#> [15,] 0 1 1 0 0 0 0 0 0 0 0 0
#> [16,] 0 1 1 0 0 0 1 0 0 0 0 0
#> [17,] 1 0 0 1 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 1 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 1 0 0 0 1 0 0
#> [20,] 0 0 1 0 0 0 1 0 0 0 0 0
#> [21,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [23,] 0 0 0 0 0 1 0 0 0 1 0 0
#> [24,] 1 0 0 0 0 0 0 0 0 0 1 1
#> [25,] 0 0 0 0 0 0 0 0 0 0 1 1
#> [26,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [27,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [30,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [31,] 0 0 1 0 0 0 0 0 0 0 1 0
#> [32,] 0 0 0 0 0 0 0 0 0 0 1 1
#> [33,] 0 0 1 0 0 0 0 1 0 0 0 0
#> [34,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 0 1 0 1 0 0 1 1 0 1 1 0
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [38,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [39,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [40,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
#> [1,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 1 0 0 0 1 0 0 0
#> [3,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [7,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [9,] 1 0 0 0 0 0 0 0 0 0 0 0
#> [10,] 1 0 0 0 0 1 0 0 0 0 0 0
#> [11,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 0 0 0 1 1 0 0 0 1 0
#> [14,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [16,] 0 1 0 0 0 1 0 1 0 0 0 0
#> [17,] 1 0 0 0 0 0 0 0 0 0 1 0
#> [18,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [20,] 0 0 0 0 1 0 0 0 0 0 1 0
#> [21,] 0 0 0 0 0 0 0 1 0 0 1 0
#> [22,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [24,] 0 0 0 0 0 1 1 0 0 0 1 0
#> [25,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [26,] 1 0 0 0 0 0 1 0 1 0 0 1
#> [27,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 1 0 0 1 0 0 0 0 0
#> [30,] 0 0 0 0 1 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 1 0 0 0 0 0 0
#> [32,] 1 0 0 1 0 0 1 0 0 0 0 0
#> [33,] 0 0 0 0 0 0 0 1 0 0 1 0
#> [34,] 1 0 0 0 0 0 0 0 1 0 0 1
#> [35,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [36,] 0 0 0 0 0 0 0 1 0 0 1 0
#> [37,] 1 0 0 0 0 0 0 0 1 0 0 1
#> [38,] 0 0 1 0 0 0 0 0 0 0 0 1
#> [39,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [40,] 0 1 0 0 0 0 0 1 1 0 0 0
#> [,38] [,39] [,40]
#> [1,] 0 0 0
#> [2,] 0 0 0
#> [3,] 1 0 0
#> [4,] 0 0 0
#> [5,] 0 0 0
#> [6,] 0 0 0
#> [7,] 0 0 0
#> [8,] 1 0 1
#> [9,] 0 0 0
#> [10,] 0 0 0
#> [11,] 0 0 0
#> [12,] 0 0 0
#> [13,] 0 0 0
#> [14,] 0 0 0
#> [15,] 0 1 0
#> [16,] 0 0 0
#> [17,] 0 0 0
#> [18,] 0 0 0
#> [19,] 0 0 0
#> [20,] 0 0 0
#> [21,] 0 0 0
#> [22,] 0 0 0
#> [23,] 0 0 1
#> [24,] 0 0 0
#> [25,] 0 0 0
#> [26,] 0 0 0
#> [27,] 0 0 1
#> [28,] 1 0 0
#> [29,] 0 0 0
#> [30,] 0 0 0
#> [31,] 0 0 0
#> [32,] 0 0 0
#> [33,] 0 0 1
#> [34,] 0 0 1
#> [35,] 0 0 0
#> [36,] 0 1 0
#> [37,] 1 0 0
#> [38,] 1 0 0
#> [39,] 0 1 0
#> [40,] 0 0 1
aa$ll
#> [1] 14.01754
## post-treatment network estimate
estimates[[2]]
#> V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 V21
#> V1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V5 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V6 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0
#> V14 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V18 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V21 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
#> V22 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V25 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V26 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V28 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V29 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V35 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V38 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 V23 V24 V25 V26 V27 V28 V29 V30 V31 V32 V33 V34 V35 V36 V37 V38 V39 V40
#> V1 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> V2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V5 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V7 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V8 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V9 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V10 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V12 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V13 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V14 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V16 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V17 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V18 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V19 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V21 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V22 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V23 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V24 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V25 0 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 0 0
#> V26 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V27 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> V28 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
#> V29 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V30 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
#> V31 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
#> V32 0 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0
#> V33 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
#> V34 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
#> V35 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> V36 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
#> V37 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
#> V38 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0
#> V39 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> V40 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## true post-treatment network
dd$network$post
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 0 0 0 1 0 0 1 0 1
#> [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 1 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0 0 0 0 1
#> [7,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [8,] 0 1 0 0 0 0 0 0 0 0 1 0 1
#> [9,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [10,] 0 0 0 0 1 0 0 0 0 0 0 0 0
#> [11,] 0 1 0 0 0 0 0 1 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [13,] 0 1 0 0 0 1 0 1 0 0 0 0 0
#> [14,] 0 0 1 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 0 0 0 0 0 0 0 0 1 1
#> [17,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [18,] 1 0 1 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 1 1 0 0 0
#> [20,] 0 0 1 0 0 0 0 0 0 0 1 0 0
#> [21,] 0 0 0 1 0 0 1 0 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 1 1 1 1 0 0 0
#> [23,] 0 0 1 0 0 1 0 0 0 0 0 0 0
#> [24,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [25,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [26,] 0 0 0 0 0 0 0 0 1 1 0 0 0
#> [27,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [28,] 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 0 0 1 0 0 0 0
#> [30,] 0 1 0 0 0 0 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 0 0 0 0 1 0 0 1
#> [32,] 0 0 0 0 0 0 1 0 0 0 0 0 1
#> [33,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [34,] 0 1 0 0 0 1 0 0 0 0 0 0 0
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 0 0 0 0 0 0 0 0 0 0 0 0 1
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [38,] 0 0 1 0 0 0 0 1 0 0 0 0 0
#> [39,] 0 0 0 0 0 0 0 0 0 0 0 0 0
#> [40,] 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25]
#> [1,] 0 0 0 0 1 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [3,] 1 0 0 0 1 0 1 0 0 1 0 0
#> [4,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 0 1 0 0
#> [7,] 0 0 0 0 0 0 0 1 1 0 0 0
#> [8,] 0 0 0 1 0 0 0 0 1 0 0 0
#> [9,] 0 0 0 0 0 1 0 0 1 0 0 0
#> [10,] 0 0 0 0 0 1 0 0 1 0 0 0
#> [11,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [12,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [14,] 0 0 0 1 0 0 0 0 0 0 1 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [16,] 0 0 0 1 0 0 1 0 0 0 0 0
#> [17,] 1 0 1 0 0 0 0 0 0 0 0 0
#> [18,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 1 0 0 1 0 0
#> [20,] 0 0 1 0 0 1 0 0 0 0 0 0
#> [21,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [22,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 1 0 0 0 0 0 0
#> [24,] 1 0 0 0 0 0 0 0 0 0 0 1
#> [25,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [26,] 0 0 0 1 0 0 0 0 0 0 0 0
#> [27,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [30,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [31,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [32,] 0 0 0 0 1 0 0 0 0 0 1 1
#> [33,] 0 0 1 0 0 0 0 1 0 0 0 0
#> [34,] 0 0 0 0 0 1 0 0 0 0 0 1
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 0 1 0 1 0 0 1 1 0 1 1 0
#> [37,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [38,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [39,] 0 1 0 0 0 0 0 0 0 0 0 0
#> [40,] 0 1 0 1 0 0 0 0 0 1 0 0
#> [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37]
#> [1,] 0 0 1 0 0 0 0 0 0 0 0 0
#> [2,] 0 0 0 0 1 0 0 0 1 0 0 0
#> [3,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [4,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [5,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [6,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [7,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [8,] 0 0 0 0 0 0 0 1 0 0 0 0
#> [9,] 1 0 0 1 0 0 0 0 0 0 0 0
#> [10,] 1 0 0 0 0 1 0 0 0 0 0 0
#> [11,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [12,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [13,] 0 0 0 0 0 1 1 0 0 0 1 0
#> [14,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [15,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [16,] 0 1 0 0 0 0 0 1 0 0 0 0
#> [17,] 1 0 0 0 0 0 0 0 0 0 1 0
#> [18,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [19,] 0 0 0 0 0 0 0 0 1 0 0 0
#> [20,] 0 0 0 0 1 0 0 0 0 0 1 0
#> [21,] 0 0 0 0 0 0 0 1 0 0 1 0
#> [22,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [23,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [24,] 0 0 0 0 0 1 1 0 0 0 1 0
#> [25,] 0 0 0 0 0 0 1 0 1 0 0 0
#> [26,] 0 0 0 0 0 0 1 0 1 0 1 1
#> [27,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [28,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [29,] 0 0 0 0 0 0 1 0 0 0 0 0
#> [30,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [31,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [32,] 1 0 0 1 0 0 0 0 0 0 0 0
#> [33,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [34,] 1 0 0 0 0 0 0 0 0 0 0 1
#> [35,] 0 0 0 0 0 0 0 0 0 0 0 0
#> [36,] 1 0 0 0 0 0 0 1 0 0 0 0
#> [37,] 1 0 0 0 0 0 0 0 1 0 0 0
#> [38,] 0 0 1 0 0 0 0 0 0 0 0 1
#> [39,] 0 0 0 0 0 0 0 0 0 0 1 0
#> [40,] 0 1 0 0 0 0 0 1 1 0 0 0
#> [,38] [,39] [,40]
#> [1,] 0 0 0
#> [2,] 0 0 0
#> [3,] 1 0 0
#> [4,] 0 0 0
#> [5,] 0 0 0
#> [6,] 0 0 0
#> [7,] 0 0 0
#> [8,] 1 0 1
#> [9,] 0 0 0
#> [10,] 0 0 0
#> [11,] 0 0 0
#> [12,] 0 0 0
#> [13,] 0 0 0
#> [14,] 0 0 0
#> [15,] 0 1 1
#> [16,] 0 0 0
#> [17,] 0 0 1
#> [18,] 0 0 0
#> [19,] 0 0 0
#> [20,] 0 0 0
#> [21,] 0 0 0
#> [22,] 0 0 0
#> [23,] 0 0 1
#> [24,] 0 0 0
#> [25,] 0 0 0
#> [26,] 0 0 0
#> [27,] 0 0 1
#> [28,] 1 0 0
#> [29,] 0 0 0
#> [30,] 0 0 0
#> [31,] 0 0 0
#> [32,] 0 0 0
#> [33,] 0 0 1
#> [34,] 0 0 1
#> [35,] 0 0 0
#> [36,] 0 1 0
#> [37,] 1 0 0
#> [38,] 0 0 0
#> [39,] 0 0 0
#> [40,] 0 0 0
## correlation parameters
model <- lm(dd$tau ~ aa$tau)
plot(aa$tau,dd$tau,xlab = "estimated tau",ylab="true tau")
abline(model, col = "red", lwd = 2)